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Fix aqe_test failures on [databricks] 14.3.
Fixes #11643. This commit fixes the AQE/DPP tests that were reported in #11643 to be failing on Databricks 14.3. This is the result of a deficient shim for GpuSubqueryBroadcastMeta being active for Databricks 14.3. The deficient shim errantly extended the non-Databricks base shim. This commit moves the commonality in Databricks shims to a common base class that is then customized for the changes in Databricks 14.3. Signed-off-by: MithunR <[email protected]>
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121
...park330db/scala/org/apache/spark/rapids/execution/GpuSubqueryBroadcastMeta330DBBase.scala
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| /* | ||
| * Copyright (c) 2024, NVIDIA CORPORATION. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| /*** spark-rapids-shim-json-lines | ||
| {"spark": "330db"} | ||
| {"spark": "332db"} | ||
| {"spark": "341db"} | ||
| {"spark": "350db143"} | ||
| spark-rapids-shim-json-lines ***/ | ||
| package org.apache.spark.sql.rapids.execution | ||
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| import com.nvidia.spark.rapids.{BaseExprMeta, DataFromReplacementRule, RapidsConf, RapidsMeta, SparkPlanMeta} | ||
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| import org.apache.spark.sql.catalyst.expressions.Expression | ||
| import org.apache.spark.sql.catalyst.plans.physical.IdentityBroadcastMode | ||
| import org.apache.spark.sql.execution.{SparkPlan, SubqueryBroadcastExec} | ||
| import org.apache.spark.sql.execution.adaptive.{BroadcastQueryStageExec} | ||
| import org.apache.spark.sql.execution.exchange.{BroadcastExchangeExec, ReusedExchangeExec} | ||
| import org.apache.spark.sql.execution.joins.HashedRelationBroadcastMode | ||
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| abstract class GpuSubqueryBroadcastMeta330DBBase(s: SubqueryBroadcastExec, | ||
| conf: RapidsConf, | ||
| p: Option[RapidsMeta[_, _, _]], | ||
| r: DataFromReplacementRule) extends | ||
| SparkPlanMeta[SubqueryBroadcastExec](s, conf, p, r) { | ||
| protected var broadcastBuilder: () => SparkPlan = _ | ||
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| override val childExprs: Seq[BaseExprMeta[_]] = Nil | ||
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| override val childPlans: Seq[SparkPlanMeta[SparkPlan]] = Nil | ||
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| override def tagPlanForGpu(): Unit = s.child match { | ||
| // DPP: For AQE off, in this case, we handle DPP by converting the underlying | ||
| // BroadcastExchangeExec to GpuBroadcastExchangeExec. | ||
| // This is slightly different from the Apache Spark case, because Spark | ||
| // sends the underlying plan into the plugin in advance via the PlanSubqueries rule. | ||
| // Here, we have the full non-GPU subquery plan, so we convert the whole | ||
| // thing. | ||
| case ex @ BroadcastExchangeExec(_, child) => | ||
| val exMeta = new GpuBroadcastMeta(ex.copy(child = child), conf, p, r) | ||
| exMeta.tagForGpu() | ||
| if (exMeta.canThisBeReplaced) { | ||
| broadcastBuilder = () => exMeta.convertToGpu() | ||
| } else { | ||
| willNotWorkOnGpu("underlying BroadcastExchange can not run in the GPU.") | ||
| } | ||
| // DPP: For AQE on, we have an almost completely different scenario then before, | ||
| // Databricks uses a BroadcastQueryStageExec and either: | ||
| // 1) provide an underlying BroadcastExchangeExec that we will have to convert | ||
| // somehow | ||
| // 2) might already do the reuse work for us. The ReusedExchange is now a | ||
| // part of the SubqueryBroadcast, so we send it back here as underlying the | ||
| // GpuSubqueryBroadcastExchangeExec | ||
| case bqse: BroadcastQueryStageExec => | ||
| bqse.plan match { | ||
| case ex: BroadcastExchangeExec => | ||
| val exMeta = new GpuBroadcastMeta(ex, conf, p, r) | ||
| exMeta.tagForGpu() | ||
| if (exMeta.canThisBeReplaced) { | ||
| broadcastBuilder = () => exMeta.convertToGpu() | ||
| } else { | ||
| willNotWorkOnGpu("underlying BroadcastExchange can not run in the GPU.") | ||
| } | ||
| case reuse: ReusedExchangeExec => | ||
| reuse.child match { | ||
| case _: GpuBroadcastExchangeExec => | ||
| // A BroadcastExchange has already been replaced, so it can run on the GPU | ||
| broadcastBuilder = () => reuse | ||
| case _ => | ||
| willNotWorkOnGpu("underlying BroadcastExchange can not run in the GPU.") | ||
| } | ||
| } | ||
| case _ => | ||
| willNotWorkOnGpu("the subquery to broadcast can not entirely run in the GPU.") | ||
| } | ||
| /** | ||
| * Simply returns the original plan. Because its only child, BroadcastExchange, doesn't | ||
| * need to change if SubqueryBroadcastExec falls back to the CPU. | ||
| */ | ||
| override def convertToCpu(): SparkPlan = s | ||
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| /** Extract the broadcast mode key expressions if there are any. */ | ||
| protected def getBroadcastModeKeyExprs: Option[Seq[Expression]] = { | ||
| val broadcastMode = s.child match { | ||
| case b: BroadcastExchangeExec => | ||
| b.mode | ||
| case bqse: BroadcastQueryStageExec => | ||
| bqse.plan match { | ||
| case b: BroadcastExchangeExec => | ||
| b.mode | ||
| case reuse: ReusedExchangeExec => | ||
| reuse.child match { | ||
| case g: GpuBroadcastExchangeExec => | ||
| g.mode | ||
| } | ||
| case _ => | ||
| throw new AssertionError("should not reach here") | ||
| } | ||
| } | ||
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| broadcastMode match { | ||
| case HashedRelationBroadcastMode(keys, _) => Some(keys) | ||
| case IdentityBroadcastMode => None | ||
| case m => throw new UnsupportedOperationException(s"Unknown broadcast mode $m") | ||
| } | ||
| } | ||
| } | ||
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